首页|University of Sumatera Utara Researchers Yield New Data on Ma- chine Learning (Identification of Rainfall events on Climate Phe- nomena in Medan based on Machine Learning)
University of Sumatera Utara Researchers Yield New Data on Ma- chine Learning (Identification of Rainfall events on Climate Phe- nomena in Medan based on Machine Learning)
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2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on artificial intelligence. According to news originating from the University of Sumatera Utara by NewsRx correspondents, research stated, “Indonesia has diverse topographical conditions that result in Indonesia having a unique climate.” Our news journalists obtained a quote from the research from University of Sumatera Utara: “One of the unique climate elements to be studied is rainfall, because rainfall has a different pattern in each region, this different rainfall pattern is caused by several climate phenomena factors that affect the rainfall pattern, including El-Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden Julian Oscillation (MJO). Medan City is the capital of North Sumatra province which is one of the areas in the flood-prone category in North Sumatra, where the factor of flooding is due to rainfall events in a long period of time, so the author wants to know which climatic phenomena factors can affect rainfall events in Medan city by using Machine Learning technology through the Matlab application, where in this study has a method by forming four combination models, namely the combination of the influence of IOD, SOI and MJO; second combination of IOD and SOI; third combination of SOI and MJO; and fourth combination of MJO and IOD, these four combinations will be the rainfall value of the four models. Furthermore, the rainfall value of the model is compared with the observed rainfall value and verification test using Mean Absolute Error (MAE) and correlation. Then the calculation of the comparison between the four rainfall models with the observed rainfall obtained the lowest MAE value during the SOI and MJO phenomenon of 15.0 mm and the highest correlation value during the IOD and SOI and SOI and MJO phenomena. So it is concluded that the combination of SOI and MJO has the best verification value.”
University of Sumatera UtaraCyborgsEmerging TechnologiesMachine Learning
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